Using customer relationship management data exhibiting unique user identifiers in a cellular network for creating geo statistical representations of the users

ABSTRACT

A computer implemented data processing system for using customer relationship management (CRM) data exhibiting unique user identifiers in a cellular network for creating geo-statistical representations of the users. The system is arranged to: repeatedly identify all network-connected devices which are both active and idle in each location area using the unique identifier; repeatedly create a table for all location areas, each table exhibiting: location area identifier, unique user identifier, time of inflow to the location area, time of outflow from the location area; and differentiate table of time N−1 over table of time N thereby detecting inflow outflow quantities of unique identifiers for each location area; decipher the difference table by the authentication center of the network; analyze the deciphered tables using CRM profiles; and join over time, the deciphered tables with corresponding location area thereby creating at least one GIS data layer.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit under 35 U.S.C. §119(e) and§120 to and through each of, and is a continuation-in-part ofapplication Ser. No. 12/365,979 filed on Feb. 5, 2009, which in turnclaimed the benefit of application Ser. No. 61/053,252 filed on May 15,2008, the content of both applications is incorporated by referenceherein it its entirety.

BACKGROUND

1. Technical Field

The present invention relates to the field of user-based cellularnetworks, and more particularly, to the extraction of tempo-spatial datarelated to users of such networks.

2. Discussion of the Related Art

Prior to setting forth the background of the related art, it may behelpful to set forth definitions of certain terms that will be usedhereinafter.

The term “user-based cellular network” as used herein in thisapplication, is defined as any network that is based upon geographicalpartition of space into cells. Each cell is provided with at least onebase station, being the end point of the network, which may communicatewith specific network-connected devices operatively associated withusers. Cellular networks may comprise cellular wireless communicationnetworks for mobile telephony, wireless internet network such as Wi-Fiand Wi-Max. Additionally, these networks further comprise network ofpayment points in stores and businesses and a network of automatedteller machines.

The term “user equipment” (UE) as used herein in this application, isany network-connected device uniquely affiliated with a particular userand therefore associated with the particular user related data, or userprofile. These network-connected devices may be, but are not limited to:cellular phones, personal device accessories (PDA), portable computerswith wireless connectivity (WiFi, WiMax etc.), payment cards (creditcards, debit cards, electronic money cards) with location identifiersand Radio frequency identification (RFID) tags.

The term “client relationship management” (CRM) as used herein in thisapplication, is defined as the processes a company uses to track andorganize its contacts with its current and prospective customers. CRMsoftware is used to support these processes; the software system can beaccessed, and information about customers and customer interactions canbe entered, stored and accessed by employees in different companydepartments. Typical CRM goals are to improve services provided tocustomers, and to use customer contact information for targetedmarketing. CRM data refers to sales, marketing, customer service,customer profile or any details on any customer contacts stored in thesystem.

Traditionally, statistics methods or any large scale marketing researchare considered human labor intensive, expensive and extensive, timeconsuming. Further limitations are that these statistics researches aremade with a relative small sample, and non up-to date or non availablefor small granularity of time-space units. Such obstacles results in anon accurate space relate data with time stamp that highly differ fromthe transaction time of the database.

BRIEF SUMMARY

According to one aspect of the invention there is provided a computerimplemented data processing system for using customer relationshipmanagement (CRM) data exhibiting unique user identifiers in a cellularnetwork comprising a plurality of location areas and further inoperative association with network-connected devices associated withusers, for creating geo-statistical representations of the users, thesystem comprising: a network-connected devices identifier; a CRM datacategorizer; and a location-based combiner. The network-connecteddevices identifier is arranged to: repeatedly identify, every a firsttime period, all network-connected devices which are both active andidle in each location area using the unique identifier; repeatedlycreate a table, every a second time period comprising a plurality of thefirst time period, for all location areas, each table exhibiting:location area identifier, unique user identifier, time of inflow to thelocation area, time of outflow from the location area; and differentiatetable of time N−1 over table of time N thereby detecting inflow outflowquantities of unique identifiers for each location area; and wherein theCRM data categorizer is arranged to: decipher the difference table bythe authentication center of the network; and analyze the decipheredtables using CRM profiles; and wherein the location-based combiner isarranged to join over time, the deciphered tables with correspondinglocation area thereby creating at least one GIS data layer.

According to another aspect of the invention there is provided a methodof using customer relationship management data exhibiting unique useridentifiers in a cellular network comprising a plurality of locationareas and further in operative association with network-connecteddevices associated with users, for creating geo-statisticalrepresentations of the users, the method comprising: repeatedlyidentifying, every a first time period, all network-connected deviceswhich are both active and idle in each location area using the uniqueidentifier; repeatedly creating a table, every a second time periodcomprising a plurality of the first time period, for all location areas,each table exhibiting: location area identifier, unique user identifier,time of inflow to the location area, time of outflow from the locationarea; differentiating table of time N−1 over table of time N therebydetecting inflow outflow quantities of unique identifiers for eachlocation area; deciphering the difference table by the authenticationcenter of the network; and analyzing the deciphered tables using CRMprofiles.

According to yet another aspect of the invention there is provided acomputer program product, comprising a computer usable medium having acomputer readable program code embodied therein, the computer readableprogram code adapted to be executed to implement a method of usingcustomer relationship management data exhibiting unique user identifiersin a cellular network comprising a plurality of location areas andfurther in operative association with network-connected devicesassociated with users, for creating geo-statistical representations ofthe users, the method comprising: repeatedly identifying, every a firsttime period, all network-connected devices which are both active andidle in each location area using the unique identifier; repeatedlycreating a table, every a second time period comprising a plurality ofthe first time period, for all location areas, each table exhibiting:location area identifier, unique user identifier, time of inflow to thelocation area, time of outflow from the location area; differentiatingtable of time N−1 over table of time N thereby detecting inflow outflowquantities of unique identifiers for each location area; deciphering thedifference table by the authentication center of the network; analyzingthe deciphered tables using CRM profiles.

These, additional, and/or other aspects and/or advantages of the presentinvention are: set forth in the detailed description which follows;possibly inferable from the detailed description; and/or learnable bypractice of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

For a better understanding of the invention and to show how the same maybe carried into effect, reference will now be made, purely by way ofexample, to the accompanying drawings in which like numerals designatecorresponding elements or sections throughout.

In the accompanying drawings:

FIG. 1 is a high level schematic block diagram of a user-based networkin communication with the data processing system according to someembodiments of the invention;

FIG. 2 is a combined data flow and data structure of the data processingsystem according to some embodiments of the invention; and

FIG. 3 is a high level flowchart illustrating the method according tosome embodiments of the invention.

The drawings together with the following detailed description makeapparent to those skilled in the art how the invention may be embodiedin practice.

DETAILED DESCRIPTION

With specific reference now to the drawings in detail, it is stressedthat the particulars shown are by way of example and for purposes ofillustrative discussion of the preferred embodiments of the presentinvention only, and are presented in the cause of providing what isbelieved to be the most useful and readily understood description of theprinciples and conceptual aspects of the invention. In this regard, noattempt is made to show structural details of the invention in moredetail than is necessary for a fundamental understanding of theinvention, the description taken with the drawings making apparent tothose skilled in the art how the several forms of the invention may beembodied in practice.

Before explaining at least one embodiment of the invention in detail, itis to be understood that the invention is not limited in its applicationto the details of construction and the arrangement of the components setforth in the following description or illustrated in the drawings. Theinvention is applicable to other embodiments or of being practiced orcarried out in various ways. Also, it is to be understood that thephraseology and terminology employed herein is for the purpose ofdescription and should not be regarded as limiting.

Embodiments of the present invention provides combining customer'sgroup's profiles data derived from the network's customer relationshipmanagement (CRM) with physical network signals and estimated locationsof the corresponding users in order to create spatio-temporaldemographic patterns. In embodiments of the invention there is providedcombination and aggregation by locations and customer's group's profilesof the data enquired via network-connected device acting as cellulardata agents over the end point of the network periodically overpredefined time intervals. The raw data is interpolated usinggeo-statistical method and results are calibrated to createspatio-temporal demographic patterns data sets.

FIG. 1 is a high level schematic block diagram of a cellular network incommunication with the data processing system according to someembodiments of the invention. Data processing system 100 comprises userequipment (UE) identifier 110, a customer relationship management (CRM)categorizer 120 and a location-based combiner 130. Data processingsystem 100 communicates with cellular network 40 which communicates witha plurality of user equipments (network-connected devices associatedwith particular users) 30A-30F via a plurality of base stations 10A, 10Band 10C, being the end points of network 40.

In operation, data processing system 100 combines and aggregateslocations and profiles classes of the data extracted fromnetwork-connected devices 30A-30F via the network and in view of thegeographic location of the cells, repeatedly over predefined timeintervals. Data processing system 100 then interpolates and overlaysgeo-statistically and calibrates the data into tempo-spatialnetwork-connected users masses patterns representations.

According to some embodiments of the invention, data processing system100 enables to locate the position of a specific provider (or roaming)UE and describe it by a tracing system.

According to some embodiments of the invention, data processing system100 aggregates any camped UE (idle or non-idle) in view of geographiclocations in order to create tempo-spatial UE masses patterns.Specifically, data processing system 100 is configured in associatedoperation with any wireless network where User Equipment (UE)communicates with a radio access network (RAN). Data processing system100 determines and records the number of any idle or non idle UE in eachcell sector (location area), aggregate the combined data by providercode into cellular provider's segments; aggregates by UE location areacoordinates and segments, thereby creating anonymous aggregated massesthat has geographical locations. Then, by repeating the aforementionedaggregation with predefined time intervals, data processing system 100creates tempo-spatial data stamps. Later, data processing system 100 maycreate, using geo-statistical methods, geographic information system(GIS) layers of the aforementioned data.

In many user-based networks, upon connection to a network, the identityof a network-connected device must be authenticated for data securityreasons. In Global System for Mobile Communications (GSM), for example,the authentication process is based on a challenge response process,wherein the network sends the Subscriber Identity Module (SIM) installedin the user equipment a random challenge. The user equipment replieswith a response according to calculations based on the random challengeand a secret key known only by the authentication center of the networkand the SIM. The response of the random challenge and the secret key iscalculated in the authentication center also. If the responsescalculated by the SIM and the authentication center are identical,mobile subscriber authenticity has been established by theauthentication process.

According to the present invention, there is provided a method ofdetermining the number of idle user equipment units in each cell. Thefocus is specifically on idle user equipment units as these units areupdating their location in predefined intervals, while user equipmentunits which are both active and idle are constantly updating thuscreating multiple signaling that has to be ignored. Embodiments of thepresent invention provide a method of counting the idle user equipmentunits in any cell taking into account the location update and theconstant inflow and out flow of users in regards to each particularcell. In GSM, for example, location update (LU) strategy can handle allthe cell phones which have been turned on and in idle status and all thecells within the GSM network are grouped into a number of disjointedlocation areas (LA).

Usually, there are three reasons which can cause one new location updaterecord, and the information can be obtained from an interface ofcellular network: A cell phone updates its location once it entersanother new location area from the old location area, and it is termedas static location update (SLU); A cell phone updates its locationperiodically every pre-specified time interval, and the time period isdetermined by the wireless carriers, and it is termed as timer-basedlocation update (TLU); A cell phone updates its location when it endsits on-going call after traversing the boundary of location area, orturns on cell phone, or sends a short message.

FIG. 2 is a high level combined data flow diagram and block diagramshowing how unique identifiers of user equipment from the CRM is used tocreate aggregated geo statistical presentation of the users in a givencellular network. There is provided a computer implemented dataprocessing system for using customer relationship management (CRM) dataexhibiting unique user identifiers in a cellular network comprising aplurality of location areas and further in operative association withnetwork-connected devices associated with users, for creatinggeo-statistical representations of the users. The system comprising: anetwork-connected devices identifier 110; a CRM data categorizer 120;and a location-based combiner 130.

In operation, network-connected devices identifier 110 is arranged to:repeatedly identify, every a first time period, all network-connecteddevices which are both active and idle in each location area using theunique identifier; repeatedly create a table, every a second time periodcomprising a plurality of the first time period, for all location areas,each table exhibiting: location area identifier, unique user identifier,time of inflow to the location area, time of outflow from the locationarea; and differentiate table of time N−1 over table of time N therebydetecting inflow outflow quantities of unique identifiers for eachlocation area; and wherein the CRM data categorizer is arranged to:decipher the difference table by the authentication center of thenetwork; and analyze the deciphered tables using CRM profiles. Thelocation-based combiner is further arranged to join over time, thedeciphered tables with corresponding location area thereby creating atleast one GIS data layer.

According to some embodiments of the invention, the analyzing thedeciphered tables using CRM profiles is preceded by categorizing andsumming the CRM data by user profiles.

According to some embodiments of the invention, the analyzing thedeciphered tables using CRM profiles is conducted such that propertiesof a particular area are used to deduce further information in relationto the users located in the particular location area.

According to some embodiments of the invention, analyzing the decipheredtables using CRM profiles is conducted such that properties of aparticular categorized user profile are used to deduce furtherinformation in relation to the particular location area in which theusers are located.

According to some embodiments of the invention, the data processingsystem further creates tempo-spatial related network-connected devicesdemographic pattern representations using spatial and temporalgeo-statistics techniques. These may include maps exhibiting GIS layersand the like.

According to some embodiments of the invention, the data processingsystem is further arranged to adjust the demographic patternrepresentations responsive to client's requirements.

FIG. 3 is a high level flowchart illustrating the method according tosome embodiments of the invention. There is provided a method of usingcustomer relationship management data exhibiting unique user identifiersin a cellular network comprising a plurality of location areas andfurther in operative association with network-connected devicesassociated with users, for creating geo-statistical representations ofthe users. The method comprising: repeatedly identifying, every a firsttime period, all network-connected devices which are both active andidle in each location area using the unique identifier 310; repeatedlycreating a table, every a second time period comprising a plurality ofthe first time period, for all location areas, each table exhibiting:location area identifier, unique user identifier, time of inflow to thelocation area, time of outflow from the location area 320;differentiating table of time N−1 over table of time N thereby detectinginflow outflow quantities of unique identifiers for each location area330; deciphering the difference table by the authentication center ofthe network; analyzing the deciphered tables using CRM profiles 340;analyzing the deciphered tables using CRM profiles 350; joining overtime, the deciphered tables with corresponding location area therebycreating at least one GIS data layer 360; and estimating globalphenomena to specific carrier network connected-devices ratios 370.

Advantageously, embodiments of the present invention enable: estimationnear real time update ratios, space and time related demographic patterndata and a uniform and repeatable method for acquiring data over wideareas. Additionally the embodiments provide a method of overcoming largeamounts of data signaling processing without slowing the cellularnetwork system and a method of extracting demographic data in a nonpervasive way to be used in demographic analysis, marketing, networkoptimization and visualization.

The availability of near real time aggregate data for areal units e.g.cells sectors (or any geographically define hot spots) enable thecreation of maps and databases relate to network-connected devicesdistribution estimation, with high granularity of time-space units.

According to some embodiments of the invention, the method furthercomprises periodically repeating the aggregating of the combined datathereby creating tempo-spatial data stamps, each exhibiting anonymousaggregated profiles classes associated with geographical locations;

According to some embodiments of the invention, the method furthercomprises estimating global phenomena in accordance with thetempo-spatial data stamps, in view of the network-connected devicesratios.

According to some embodiments of the invention, the method furthercomprising creating, using geo-statistical methods a geographicinformation system (GIS) layer presenting the anonymous aggregatedprofiles classes associated with geographical locations.

Advantageously, embodiments of the present invention providenon-pervasive sampling method and data processing system enabling toidentify and relate customer into a predefined group profiles withoutoverloading the network signaling flow.

Advantageously, the data processing system, computer implemented methodand computer program described herein may be used in demographicanalysis, marketing, cellular provider network optimization andvisualization and combining cellular devices data records with GIS andstatistical process.

Advantageously, the availability of up-to-date aggregated data for realunits e.g. cells sectors (any geographically define hot spots) enablethe creation of maps and databases related to provider's market sharedistribution estimation exhibiting high granularity of time-space units.

The availability of up-to-date aggregate data for real units e.g. cellssectors (any geographically define hot spots) enable the creation ofmaps and databases relate to network connected devices (population)distribution estimation with high granularity of time-space units.

Advantageously, use any network related system provider that can locategeographically a device and aggregate the data related to the device bytempo-spatial patterns. Examples for such alternatives can be: ATMstempo-spatial patterns activity, and distribution of active TV's at homeby place and time of the day.

According to some embodiments of the invention, the system can beimplemented in digital electronic circuitry, or in computer hardware,firmware, software, or in combinations thereof.

Suitable processors may be used to implement the data processing system,computer implemented method and computer program product. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for executing instructions and one or more memories forstoring instructions and data. Generally, a computer will also include,or be operatively coupled to communicate with, one or more mass storagedevices for storing data files. Storage devices suitable for tangiblyembodying computer program instructions and data include all forms ofnon-volatile memory, including by way of example semiconductor memorydevices, such as EPROM, EEPROM, and flash memory devices.

In the above description, an embodiment is an example or implementationof the inventions. The various appearances of “one embodiment,” “anembodiment” or “some embodiments” do not necessarily all refer to thesame embodiments.

Although various features of the invention may be described in thecontext of a single embodiment, the features may also be providedseparately or in any suitable combination. Conversely, although theinvention may be described herein in the context of separate embodimentsfor clarity, the invention may also be implemented in a singleembodiment.

Reference in the specification to “some embodiments”, “an embodiment”,“one embodiment” or “other embodiments” means that a particular feature,structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments, of the inventions.

It is to be understood that the phraseology and terminology employedherein is not to be construed as limiting and are for descriptivepurpose only.

The principles and uses of the teachings of the present invention may bebetter understood with reference to the accompanying description,figures and examples.

It is to be understood that the details set forth herein do not construea limitation to an application of the invention.

Furthermore, it is to be understood that the invention can be carriedout or practiced in various ways and that the invention can beimplemented in embodiments other than the ones outlined in thedescription above.

It is to be understood that the terms “including”, “comprising”,“consisting” and grammatical variants thereof do not preclude theaddition of one or more components, features, steps, or integers orgroups thereof and that the terms are to be construed as specifyingcomponents, features, steps or integers.

If the specification or claims refer to “an additional” element, thatdoes not preclude there being more than one of the additional element.

It is to be understood that where the claims or specification refer to“a” or “an” element, such reference is not be construed that there isonly one of that element.

It is to be understood that where the specification states that acomponent, feature, structure, or characteristic “may”, “might”, “can”or “could” be included, that particular component, feature, structure,or characteristic is not required to be included.

Where applicable, although state diagrams, flow diagrams or both may beused to describe embodiments, the invention is not limited to thosediagrams or to the corresponding descriptions. For example, flow neednot move through each illustrated box or state, or in exactly the sameorder as illustrated and described.

Methods of the present invention may be implemented by performing orcompleting manually, automatically, or a combination thereof, selectedsteps or tasks.

The term “method” may refer to manners, means, techniques and proceduresfor accomplishing a given task including, but not limited to, thosemanners, means, techniques and procedures either known to, or readilydeveloped from known manners, means, techniques and procedures bypractitioners of the art to which the invention belongs.

The descriptions, examples, methods and materials presented in theclaims and the specification are not to be construed as limiting butrather as illustrative only.

Meanings of technical and scientific terms used herein are to becommonly understood as by one of ordinary skill in the art to which theinvention belongs, unless otherwise defined.

The present invention may be implemented in the testing or practice withmethods and materials equivalent or similar to those described herein.

Any publications, including patents, patent applications and articles,referenced or mentioned in this specification are herein incorporated intheir entirety into the specification, to the same extent as if eachindividual publication was specifically and individually indicated to beincorporated herein. In addition, citation or identification of anyreference in the description of some embodiments of the invention shallnot be construed as an admission that such reference is available asprior art to the present invention.

While the invention has been described with respect to a limited numberof embodiments, these should not be construed as limitations on thescope of the invention, but rather as exemplifications of some of thepreferred embodiments. Other possible variations, modifications, andapplications are also within the scope of the invention. Accordingly,the scope of the invention should not be limited by what has thus farbeen described, but by the appended claims and their legal equivalents.

1. A computer implemented data processing system for using customerrelationship management (CRM) data exhibiting unique user identifiers ina cellular network comprising a plurality of location areas and furtherin operative association with network-connected devices associated withusers, for creating geo-statistical representations of the users, thesystem comprising: a network-connected devices identifier; a CRM datacategorizer; and a location-based combiner, wherein the anetwork-connected devices identifier is arranged to: repeatedlyidentify, every a first time period, all network-connected devices whichare both active and idle in each location area using the uniqueidentifier; repeatedly create a table, every a second time periodcomprising a plurality of the first time period, for all location areas,each table exhibiting: location area identifier, unique user identifier,time of inflow to the location area, time of outflow from the locationarea; and differentiate table of time N−1 over table of time N therebydetecting inflow outflow quantities of unique identifiers for eachlocation area; and wherein the CRM data categorizer is arranged to:decipher the difference table by the authentication center of thenetwork; and analyze the deciphered tables using CRM profiles; andwherein the location-based combiner is arranged to join over time, thedeciphered tables with corresponding location area thereby creating atleast one GIS data layer.
 2. The data processing system according toclaim 1, wherein the location-based combiner is further arranged toestimate global phenomena to specific carrier network connected-devicesratios.
 3. The data processing system according to claim 1, wherein theCRM data categorizer analyzes the deciphered tables using CRM profilesby categorizing and summing the CRM data by user profiles.
 4. The dataprocessing system according to claim 1, wherein the CRM data categorizeranalyzes the deciphered tables using CRM profiles is conducted such thatproperties of a particular area are used to deduce further informationin relation to the users located in the particular location area.
 5. Thedata processing system according to claim 1, wherein the CRM datacategorizer analyzes the deciphered tables using CRM profiles such thatproperties of a particular categorized user profile are used to deducefurther information in relation to the particular location area in whichthe users are located.
 6. A method of using customer relationshipmanagement data exhibiting unique user identifiers in a cellular networkcomprising a plurality of location areas and further in operativeassociation with network-connected devices associated with users, forcreating geo-statistical representations of the users, the methodcomprising: repeatedly identifying, every a first time period, allnetwork-connected devices which are both active and idle in eachlocation area using the unique identifier; repeatedly creating a table,every a second time period comprising a plurality of the first timeperiod, for all location areas, each table exhibiting: location areaidentifier, unique user identifier, time of inflow to the location area,time of outflow from the location area; differentiating table of timeN−1 over table of time N thereby detecting inflow outflow quantities ofunique identifiers for each location area; deciphering the differencetable by the authentication center of the network; and analyzing thedeciphered tables using CRM profiles.
 7. The method according to claim6, further comprising joining over time, the deciphered tables withcorresponding location area thereby creating at least one GIS datalayer.
 8. The method according to claim 7, further comprising estimatingglobal phenomena to specific carrier network connected-devices ratios.9. The method according to claim 6, wherein analyzing the decipheredtables using CRM profiles is preceded by categorizing and summing theCRM data by user profiles.
 10. The method according to claim 9, whereinanalyzing the deciphered tables using CRM profiles is conducted suchthat properties of a particular area are used to deduce furtherinformation in relation to the users located in the particular locationarea.
 11. The method according to claim 9, wherein analyzing thedeciphered tables using CRM profiles is conducted such that propertiesof a particular categorized user profile are used to deduce furtherinformation in relation to the particular location area in which theusers are located.
 12. A computer program product, comprising a computerusable medium having a computer readable program code embodied therein,the computer readable program code adapted to be executed to implement amethod of using customer relationship management data exhibiting uniqueuser identifiers in a cellular network comprising a plurality oflocation areas and further in operative association withnetwork-connected devices associated with users, for creatinggeo-statistical representations of the users, the method comprising:repeatedly identifying, every a first time period, all network-connecteddevices which are both active and idle in each location area using theunique identifier; repeatedly creating a table, every a second timeperiod comprising a plurality of the first time period, for all locationareas, each table exhibiting: location area identifier, unique useridentifier, time of inflow to the location area, time of outflow fromthe location area; differentiating table of time N−1 over table of timeN thereby detecting inflow outflow quantities of unique identifiers foreach location area; deciphering the difference table by theauthentication center of the network; and analyzing the decipheredtables using CRM profiles.
 13. The computer program product according toclaim 12, wherein the method further comprising further comprisingjoining over time, the deciphered tables with corresponding locationarea thereby creating at least one GIS data layer.
 14. The computerprogram product according to claim 12, further comprising estimatingglobal phenomena to specific carrier network connected-devices ratios.15. The computer program product according to claim 12, whereinanalyzing the deciphered tables using CRM profiles is preceded bycategorizing and summing the CRM data by user profiles.
 16. The computerprogram product according to claim 12, wherein analyzing the decipheredtables using CRM profiles is conducted such that properties of aparticular area are used to deduce further information in relation tothe users located in the particular location area.
 17. The computerprogram product according to claim 12, wherein analyzing the decipheredtables using CRM profiles is conducted such that properties of aparticular categorized user profile are used to deduce furtherinformation in relation to the particular location area in which theusers are located.